Comparison
of ground-based GPS precipitable water vapour to independent
observations and Numerical Weather Prediction model reanalyses over
Africa.
Bock, O. (1), M.-N. Bouin (2), A. Walpersdorf (3), J.P. Lafore (4), S. Janicot (5), F. Guichard (4), A. Agusti-Panareda (6)
Quart. J. Roy. Meteor. Soc., 133, 2011-2027, 2007
1 IPSL/SA, Université Paris VI, France
2 LAREG, IGN, France
3 LGIT, CNRS, France
4 CNRM/GMME, Météo-France, France
5 IPSL/LOCEAN, Université Paris VI, France
6 ECMWF, Shinfield Park, Reading, England
This study aims at assessing the
consistency between different precipitable water vapour (PWV) datasets
over Africa (between 10°S and 35°N). This region is
characterized by large spatial and temporal variability of humidity but
also by the scarcity of its operational observing network limiting our
knowledge of the hydrological cycle. We inter-compare data from
observing techniques such as ground-based Global Positioning System
(GPS), radiosondes, AERONET sun photometers and SSM/I, as well as
reanalyses from European Centre for Medium-Range Weather Forecasts
(ERA40) and National Center for Environmental Prediction (NCEP2). The
GPS data, especially, are a new source of PWV observation in this
region. PWV estimates from nine ground-based GPS receivers of the
international GPS network data are used as a reference dataset to which
the others are compared. Good agreement is found between observational
techniques, though dry biases of 12-14% are evidenced in radiosonde
data at three sites. Reasonable agreement is found between the
observational datasets and ERA40 (NCEP2) reanalyses with maximum bias
< 9% (14%) and standard deviation < 17% (20%). Since GPS
data were not assimilated in the ERA40 and NCEP2 reanalyses, they allow
for a fully independent validation of the reanalyses. They highlight
limitations in the reanalyses, especially at timescales from sub-daily
to periods of a few days. This work also demonstrates the high
potential of GPS PWV estimates over Africa for the analysis of the
hydrological cycle, at timescales ranging between sub-diurnal to
seasonal. Such observations can help studying atmospheric processes
targeted by the African Monsoon Multidisciplinary Analysis (AMMA)
project.
Keywords: GPS, precipitable water, Africa, Monsoon.